11/Jul/2025
Analysis of the distribution of health services in the State of São Paulo: focus on Big Data
DOI: 10.31744/einstein_journal/2025AO1070
Highlights ■ The extract, transform, and load algorithm automates data extraction and updates in the PostgreSQL database. ■ The interactive dashboard enables detailed queries on establishments and professionals. ■ Results highlight medical doctor deficit in 22 cities and a shortage of community agents. ■ The tool can scale and assist managers in resource allocation for healthcare. ABSTRACT Objective: To develop a process (pipeline) for extracting, processing, and analyzing data from the National Registry of Health Establishments in the State of […]
Keywords: Apache Spark; Big data; CNES; Dashboard systems; Database; Geographic locations; Health facilities; Health personnel; Health Services Accessibility; PostgreSQL; Power BI; Public health
26/Feb/2024
Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?
einstein (São Paulo). 26/Feb/2024;22:eAO0328.
View Article26/Feb/2024
Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?
DOI: 10.31744/einstein_journal/2024AO0328
Highlights Developed models to forecast bed occupancy for up to 14 days and monitored errors for 365 days. Telemedicine calls from COVID-19 patients correlated withthe number of patients hospitalized in the next 8 days. ABSTRACT Objective: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. Methods: Two main models were developed. The first model calculated hospital occupation as […]
Keywords: Big data; Coronavirus infections; COVID-19; Decision support systems, clinical; Forecasting; Pandemics; Resource allocation; Telemedicine
03/Aug/2023
Proposed public policies to improve outcomes in vascular surgery: an experts’ forum
DOI: 10.31744/einstein_journal/2023AE0241
Highlights Notification of complications of arterial surgeries is essential in identifying strategies to improve surgical outcomes. Screening of prevalent and/or morbid diseases allows early intervention and prevention of complications. Use of telemedicine in vascular follow-up allows optimizing the use of resources and reducing the burden on health services. Concentrating complex cases in reference hospitals leads to improved surgical outcomes. ABSTRACT Objective To evaluate outcomes of vascular surgeries and identify strategies to improve public vascular care. Methods This was a descriptive, […]
Keywords: Amputation, surgical; Big data; Carotid artery diseases; Endovascular procedures; Health policy; Peripheral arterial disease; Public Policy; Vascular diseases; Vascular surgical procedures
28/Apr/2022
Eye diseases during pregnancy: a study with the medical data warehouse in the eye clinic of the Ludwig-Maximilians-Universität München in Munich in Germany
einstein (São Paulo). 28/Apr/2022;20:eAO6613.
View Article28/Apr/2022
Eye diseases during pregnancy: a study with the medical data warehouse in the eye clinic of the Ludwig-Maximilians-Universität München in Munich in Germany
DOI: 10.31744/einstein_journal/2022AO6613
ABSTRACT Objective To analyze the most common ophthalmologic disorders in pregnant women seen in a hospital in Munich in Germany using a big data analysis system, as well as to compare the results obtained with those from other epidemiological studies that used different data acquisition methods. Methods We retrospectively analyzed electronic health records of pregnant women who were seen at the ophthalmology department from 2003 to 2019 at the Ludwig-Maximilians-Universität München hospital. The main complaints that led to ophthalmic consultations […]
Keywords: Big data; Data warehousing; Eye diseases/complications; Pregnancy complications
25/Apr/2022
Headache and rhinitis: pattern search on Google Trends for 17 years
einstein (São Paulo). 25/Apr/2022;20:eAO6224.
View Article25/Apr/2022
Headache and rhinitis: pattern search on Google Trends for 17 years
DOI: 10.31744/einstein_journal/2022AO6224
ABSTRACT Objective Headache and rhinitis are highly prevalent and comorbid. The objective of the present study is to analyze the correlation of headache and rhinitis, in addition to the temporal pattern of these diseases in 17 years, using the Google Trends platform. Methods Google Trends was searched from January 2004 to June 2021, using the entry: [“rinite” (rhinitis) + “dor de cabeça” (headache)” + “Alzheimer” + “enxaqueca” (migraine)]. Migraine, primary headache, and Alzheimer’s, with no clear relation with headache, were […]
Keywords: Alzheimer disease; Big data; Epidemiology; Headache; Migraine disorders; Rhinitis